# Core 03: Tumor Imaging Metrics

> **NIH NIH P30** · DANA-FARBER CANCER INST · 2021 · $178,466

## Abstract

Tumor Imaging Metrics Shared Resource
Project Summary / Abstract
The Tumor Imaging Metrics Core provides objective assessment of tumor response to treatment for patients
enrolled in oncology clinical trials. All major radiological assessment criteria are supported including: RECIST
(1.0 and 1.1), Cheson (2007 and 2009), IWCLL, RANO, PET SUV, PCWG2, Choi, 3D Volume, and irRC. For
each patient, target and non-target lesions are selected according to the assessment criteria guidelines and
are tracked longitudinally. Users are able to log into the website from anywhere at any time to access data and
order a request for scan analysis. Quantitative analysis of CT, MR, and PET imaging studies are performed on
a variety of modality-specific workstations. After scans are analyzed, the measurement results are reviewed
and finalized by Harvard faculty radiologists and/or nuclear medicine physicians. Measurement results are
stored in the Core database on a secure website and are viewable online by authorized trial staff. The
quantitative measurements are used to determine tumor response to treatment and ultimately guide patient
care. Summary statistics for the trial are presented as well as individual patient measurements. Rates for
services are very reasonable compared to other options available from outside DF/HCC.

## Key facts

- **NIH application ID:** 10062885
- **Project number:** 5P30CA006516-56
- **Recipient organization:** DANA-FARBER CANCER INST
- **Principal Investigator:** GORDON J HARRIS
- **Activity code:** P30 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $178,466
- **Award type:** 5
- **Project period:** 1997-03-10 → 2021-11-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10062885

## Citation

> US National Institutes of Health, RePORTER application 10062885, Core 03: Tumor Imaging Metrics (5P30CA006516-56). Retrieved via AI Analytics 2026-05-21 from https://api.ai-analytics.org/grant/nih/10062885. Licensed CC0.

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